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We study the value of a two-player zero-sum game on a random matrix $M\in \mathbb{R}^{n\times m}$, defined by $v(M) = \min_{x\in\Delta_n}\max_{y\in \Delta_m}x^T M y$. In the setting where $n=m$ and $M$ has i.i.d. standard Gaussian entries,…

Probability · Mathematics 2026-01-13 Romain Cosson , Laurent Massoulié

This paper studies two-player zero-sum repeated Bayesian games in which every player has a private type that is unknown to the other player, and the initial probability of the type of every player is publicly known. The types of players are…

Computer Science and Game Theory · Computer Science 2017-11-08 Lichun Li , Cedric Langbort , Jeff Shamma

Game-theoretic probability uses the structure of gambles to define a concept like probability, but which is more flexible and robust. We show that results in game-theoretic probability can be thought of as minimax theorems for specific…

Probability · Mathematics 2025-12-25 Rafael Frongillo

The notion of optimality naturally arises in many areas of applied mathematics and computer science concerned with decision making. Here we consider this notion in the context of two formalisms used for different purposes and in different…

Artificial Intelligence · Computer Science 2008-10-17 Krzysztof R. Apt , Francesca Rossi , K. Brent Venable

Learning heuristics for combinatorial optimization problems through graph neural networks have recently shown promising results on some classic NP-hard problems. These are single-level optimization problems with only one player. Multilevel…

Machine Learning · Computer Science 2023-04-22 Adel Nabli , Margarida Carvalho

The paper is devoted to the first-order mean field game system in the case when the distribution of players can contain atoms. The proposed definition of a generalized solution is based on the minimax approach to the Hamilton-Jacobi…

Analysis of PDEs · Mathematics 2014-04-21 Yurii Averboukh

We consider multiple-environment Markov decision processes (MEMDP), which consist of a finite set of MDPs over the same state space, representing different scenarios of transition structure and probability. The value of a strategy is the…

Logic in Computer Science · Computer Science 2025-04-23 Krishnendu Chatterjee , Laurent Doyen , Jean-François Raskin , Ocan Sankur

A classic model to study strategic decision making in multi-agent systems is the normal-form game. This model can be generalised to allow for an infinite number of pure strategies leading to continuous games. Multi-objective normal-form…

Computer Science and Game Theory · Computer Science 2023-03-02 Willem Röpke , Carla Groenland , Roxana Rădulescu , Ann Nowé , Diederik M. Roijers

We consider a sub-class of bi-matrix games which we refer to as two-person (hereafter referred to as two-player) additively-separable sum (TPASS) games, where the sum of the pay-offs of the two players is additively separable. The row…

Optimization and Control · Mathematics 2025-11-03 Somdeb Lahiri

A new game theoretical solution concept for open spectrum sharing in cognitive radio (CR) environments is presented, the Lorenz equilibrium (LE). Both Nash and Pareto solution concepts have limitations when applied to real world problems.…

Adaptation and Self-Organizing Systems · Physics 2013-04-08 Ligia Cremene , D. Dumitrescu

Variational inequalities are modelling tools used to capture a variety of decision-making problems arising in mathematical optimization, operations research, game theory. The scenario approach is a set of techniques developed to tackle…

Optimization and Control · Mathematics 2020-03-17 Dario Paccagnan , Marco C. Campi

Concurrent multi-player mean-payoff games are important models for systems of agents with individual, non-dichotomous preferences. Whilst these games have been extensively studied in terms of their equilibria in non-cooperative settings,…

Computer Science and Game Theory · Computer Science 2023-11-28 Julian Gutierrez , Anthony W. Lin , Muhammad Najib , Thomas Steeples , Michael Wooldridge

Graph games provide the foundation for modeling and synthesizing reactive processes. In the synthesis of stochastic reactive processes, the traditional model is perfect-information stochastic games, where some transitions of the game graph…

Logic in Computer Science · Computer Science 2016-04-22 Krishnendu Chatterjee , Laurent Doyen

In several standard models of dynamic programming (gambling houses, MDPs, POMDPs), we prove the existence of a very robust notion of value for the infinitely repeated problem, namely the pathwise uniform value. This solves two open…

Optimization and Control · Mathematics 2015-09-09 Xavier Venel , Bruno Ziliotto

We study an original problem of pure exploration in a strategic bandit model motivated by Monte Carlo Tree Search. It consists in identifying the best action in a game, when the player may sample random outcomes of sequentially chosen pairs…

Statistics Theory · Mathematics 2016-02-16 Aurélien Garivier , Emilie Kaufmann , Wouter Koolen

Dynamic zero-sum games are an important class of problems with applications ranging from evasion-pursuit and heads-up poker to certain adversarial versions of control problems such as multi-armed bandit and multiclass queuing problems.…

Computer Science and Game Theory · Computer Science 2015-06-12 Martin Haugh , Chun Wang

Markov decision processes (MDPs) are a popular model for performance analysis and optimization of stochastic systems. The parameters of stochastic behavior of MDPs are estimates from empirical observations of a system; their values are not…

Artificial Intelligence · Computer Science 2017-10-26 Dimitri Scheftelowitsch , Peter Buchholz , Vahid Hashemi , Holger Hermanns

A multicriteria economic problem is considered: the basic production assets and the labor resources define a set of feasible solutions (alternatives), labor costs, costs of the basic production assets (to be minimized), and cost of the…

Optimization and Control · Mathematics 2018-05-29 Aleksey Zakharov

Nonzero-sum stochastic differential games with impulse controls offer a realistic and far-reaching modelling framework for applications within finance, energy markets, and other areas, but the difficulty in solving such problems has…

Numerical Analysis · Mathematics 2020-06-29 Diego Zabaljauregui

In multiparty multiobjective optimization problems, solution sets are usually evaluated using classical performance metrics, aggregated across DMs. However, such mean-based evaluations may be unfair by favoring certain parties, as they…

Neural and Evolutionary Computing · Computer Science 2026-02-02 Zifan Zhao , Peilan Xu , Wenjian Luo
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